188 citations · 486 across the 25 of their papers we have counts for
6 papers · 1 filter
Adaptivity is all you need: Optimal stabilizer learning using just single-copy measurements
L. Bittel, J. Eisert, W. Gong +2
Stabilizer states are central to quantum computing, underlying quantum error correction, benchmarking, and efficient classical simulation. Yet their learnability exhibits a strikin…
Testing quantum Gaussianity with constant sample complexity
Mahtab Yaghubi Rad, Ricard Puig, Saksham Hassanandani +4
Efficiently testing whether a quantum state possesses a given structure is both a fundamental and a practical task in quantum information. Among the most important structured famil…
Towards verifiable quantum advantage with random circuits: Observables that survive concentration
Antonio A. Mele, Francesco A. Mele, Jarrod R. McClean +1
Demonstrating quantum advantage on current quantum hardware is a central goal of quantum computing, and random quantum circuits underpin many leading proposals. Yet sampling-based…
When are bosonic Gaussian states classical to learn?
Senrui Chen, Antonio Anna Mele, Francesco Anna Mele +1
A fundamental question in physics is: When does classical behavior emerge from quantum systems? Bosonic Gaussian states provide a natural setting to explore this quantum-classical…
Strong unitary designs in optimal depth and space
Teodor Parella-Dilmé, Júlia Barberà-Rodríguez, Salvatore F. E. Oliviero +1
Unitary designs provide finite-moment approximations to Haar-random unitaries, with wide-ranging applications across physics and quantum information, from scrambling and black-hole…
Quantum memory advantage for quantum process tomography
Carlos Bravo-Prieto, Weiyuan Gong, Antonio Anna Mele
Quantum process tomography, the task of learning an unknown quantum channel from black-box access, is a central problem in quantum information. In this setting, protocols with quan…